GMGhanashyama Mahanty: At Citi our core aim is to help our clients achieve their financial goals. In the current competitive landscape, this is possible, provided one has a proper organizational framework to quickly and effectively understand clients’ needs and deliver meaningful solution in time.
Analytics is serious business at Citi. We are an insight driven organization. We have number of facilities around the Globe that produce customer insights which is used in the decision making process around acquisition, portfolio management and retention activities. There is a heavy use of analytics in the new product development and value proposition refinement areas.
AIM: How do you see Analytics evolving today in the industry as a whole? What are the most important contemporary trends that you see emerging in the Analytics space across the globe?
GM: Its a fast growing industry. Business leaders urging to take decisions based on facts and figures as oppose to guesswork as has been in the past. Earlier, analytics was restricted to selective set of industries. Today, you have industries like beauty care and tourism started using analytics for relationship management activities.
There are two areas in focus today. First, insights driven decision latency is synonymous with lost opportunity today. There is a huge focus on how to close the gap between receiving insights and taking sales and service actions on the same. Cloud computing and real time decisioing and offering system belong to this area. Second, historically we have been looking at post facto transactional behavior, coming in a very structured format, to observe consumer needs. New media technology capturing a lot of information about consumer values, lifestyle, preference, intentions and recommendations comes from disparate sources and voluminous in size. This is called the “big data” which is gaining momentum now.
AIM: Do you envisage Analytics reaching a level of standardization in near future, where solutions can be deployed on a ‘plug-and-play’ basis without having to deal with complexities and nuances of an industry?
GM: I would shy away from saying so. Analytics is a very complex domain. There are industry specific nuisance that should be taken care of while designing a solution to get true incremental advantage. Some solution providers have attempted to standardize solutions though I am not very familiar with their success rate.
There are certainly some operational analytic areas where possibly one can follow a “plug-and-play” approach but difficult to generalize across industries. Technology is great facilitator but human touch is very important in deriving inference out of data. This is one of the reasons why so many retail, telecom and finance/banking giants got an embedded analytics department within the company. Analytics is considered as important vertical at Citi.
AIM: Customer data collection process is still in a very nascent stage in India. How do you see this evolving in the near future?
GM: This is indeed true. Very difficult to assign a clear reason except saying that from a producer and trader prospective it was not economically viable to do before. There are other pre-conditions to be met to have this process in place.
India got a huge emerging consumer base. Given new technologies, both producer and consumer are keen to know each other’s need better – as there is way to do so now. Government is busy in facilitating this process by creating unique identification profile for consumer. Consumer credit bureau gaining momentum in the country. We are in the right track to follow developed consumer markets. A lot more investment is expected in coming years in this area.
AIM: What are the most significant challenges you face being in the forefront of analytics space?
GM: There are mainly three challenges that I have encountered throughout my decade long journey in this space. First, not enough skill and talent to translate business problem into right analytical solution and benefits to business. This is a serious issue and often discourages senior management sponsorship in this area. Second, this being a backend support function, we don’t see much investment towards nourishing and nurturing analytic talent which leads to poor job satisfaction and high attrition rate. Third, we have moved away from consumer communication to interaction framework. This mean there is proliferation of interaction channels which is producing huge volume of data in different form and shape. Simpler interface needs to be built between technology and measurement science to better leverage analytic talents
AIM: What do you suggest to new graduates aspiring to get into analytics space?
GM: Analytics is the sexiest job of the 21st century. Its industry agnostic and got a wide range of applicability starting from beauty care, gambling, retailing to mighty financial/banking industries. This is the best job for an inquisitive mind as it allows one forming theories, testing hypothesis and predicting future paths. Early exposure and experience in this domain makes you a better resource in Risk, Marketing and Business Planning and Analysis (BP&A) functions.
A basic degree in any near computational science like Mathematics, Statistics, Operational Research, Computer Science, Economics, Econometrics or Business Administration will make you eligible for this job. To excel, one needs to have a good familiarity towards statistical methods and measurement kits, database technologies, reporting and visualization tools. Of course, a strong knack towards playing around with gigs and gigs of data is a precondition to enjoy in this function.